Thanks to the recent improvements in microelectronics and communication systems, a large number of devices and objects have been embedded with electronics, software sensor, and connectivity means that allow them to collect and exchange information. This network of objects, is called the Internet of Things, or IoT.
IoT objects are often simple devices with modest energy resources, as they must rely on local accumulators or energy harvesting. They need therefore wireless connectivity solutions that agree with these conditions.
Low-throughput long-distance wireless networks are particularly suited to applications in the IoT, in particular where low power, long battery autonomy and low cost are sought. The LoRa communication system, known among others by patent applications EP2767847 and EP2449690, uses chirp spread-spectrum modulation to achieve these goals.
Localization is one of the key enablers for the development of the Internet of Things. There is a need for low-power, low-complexity localization methods and devices for mobile nodes.
Satellite localization systems are known since a considerable time. GP, Glonass and Galileo allow precise self-localization of mobile nodes, based on the precise timing of signals received from a constellation of space vehicles whose orbits are precisely known.
Although these systems have been extremely successful in many ways, they are not so well suited to the low-power range segment of the IoT. In particular the initial acquisition of the signals demands a considerable computing power, and indoor reception is still very difficult. Terrestrial or maritime localization systems based on the timing of radio signals are also known, predating the satellite-systems, and are still used today.
Radio-based localization often derives the position of an object from the measured times of arrival of a radio signal linking the object to some reference whose position is known. In the LoRa system, the time of arrival of a signal can be determined with methods that exploit the duality between time and frequency in chirp-modulation, as known from EP2767848 and EP2767847.
Both device-side localization and network-side localization methods are known in the art. In device-side localization, which is the variant used, for example in GPS, the device itself receives the radio signals from a number of beacons and, by timing them, determines the ranges to the beacons and its own location, without further external assistance whereas, in network-side localization, the device whose position is requested sends one or several signals that is received from a plurality of fixed stations, belonging to the network infrastructure. The ranges and the location are computed in the network infrastructure.
Both methods have advantages and shortcomings. Network-side localization, however, transfers most of the computations in the networks structure, which allows a simplification of the end node's hardware. Network-side localization permits the localization of transmit-only nodes and is harder to jam than the device-side variant, which is an advantage in security applications.
Both variants of localization, however, depend on determining accurately the time of arrival of radio signals. Multipath is ever present in real communication channels and it degrade the accuracy of timing. There is therefore a need of methods and systems for timing a radio signal that is more robust to multipath than the ones of the state of the art.
Timing a radio signal often involves determining its position on an absolute time axis, determined by an accurate clock, for example a GPS-disciplined clock, or the time difference of arrival between two similar signals. In both cases, the larger the bandwidth of the signal, the easier the localization will be. While a zero-bandwidth CW signal has no time structure and is essentially impossible to time precisely, radar system achieve excellent timing by using very short broad bandwidth radio pulses.
LoRa is a spread spectrum modulation. Its bandwidth, however, is relatively small: about 125 kHz in most cases, in contrast with radar systems that use some tens of MHz up to several GHz of bandwidth. Therefore, the techniques derived from radar applications are not really effective for LoRa signals. In particular, LoRa signals last much longer, and the structure of the signals does not allow resolving multipath in the time domain.
Effective localization requires in general a time-of-arrival accuracy of 30 to 300 ns, depending on the propagation conditions and on the precision sought for. With a bandwidth of 125 kHz, the Nyquist sampled data has a resolution of 8 microseconds, about 250 times larger than the target resolution.
Since LoRa is chirp-based spread spectrum modulation, the time of arrival can be estimated from the frequency of the incoming signal which, due to multipath, will be a superposition of several complex exponential signals. Algorithms to extract individual components from such a superposition are known, for example the super-resolution MUSIC algorithm. These methods, however, are computationally very intensive, particularly, in our case, where the vectors can be very long, and the number of multipath components is not known in advance.
US2014064337 and WO0002325 describe receivers using chirps for synchronization.